CAJ | 학술논문

目的应用系统生物学方法,研发一种基于转录组表达谱的基因网络可视化工具,以直观显示急性心肌梗死后早期的转录组和代谢调控的整体变化.方法在美国国立卫生研究中心(NCBI) GEO数据库下载编号为GDS2331的一个急性心肌梗死后大鼠心脏左心室的基因芯片表达文件,其平台编号为GPL83.筛选实验时间在15 min,60 min,4h,12h,24和48 h的假手术和急性心肌梗死模型亚组数据,利用Mathwork bioinformatics toolbox工具包将数据转化为计算机可读的结构体.利用模式识别算法剔除表达背景噪声；最后获得心肌梗死建模后表达模式扰动最明显的基因谱.利用K-mean算法对这些基因进行分类,并进行基因本体分析(gene ontology,GO).进而将有关通路标定在京都基因和基因组百科数据库(kyoto encyclopedia of genes and genomes,KEGG)中,形成基因组-表达谱系统分析.结果共有1400个基因被筛选出来.在损伤后的前48 h,这些基因的变化模式可归为16类.根据可以获得基因本体分析发现:在生物学过程上,心肌梗死后早期调控发生改变主要和发育基因相关,其中主要包括蛋白激酶B信号传导途径,中枢神经系统发育途径,以及cytochalasin B调控相关途径.在分子功能上,这些功能主要和磷酸化,肌动蛋白的结合以及核酸的配对解离有关.在细胞成分上,主要与细胞内外膜相结构之间的联系、高尔基复合体、出胞作用、以及细胞骨架特别是dynactin complex等结构有关.KEGG作图标记可显示在分子调控传导路径当中,受到影响的基因很可能通过该传导通路的上下游分子进行调控.如以肌动蛋白为核心的细胞骨架信息传导途径的调控中,GF RTK Vav/tiam Rac mlCK Myosin整个调控途径中的分子都有相同的调控模式.结论利用系统生物学技术可以实现急性心肌梗死后基因表达波动模式的可视化描述.这些模式可以反映基因表达在不同时间点质和量上的表达差异.结合Geneontology的基因语义功能学上的研究和基于KEGG的作图法是一种有力的联合分析工具,前者可以直观的展示扰动的基因在功能上的共同点,后者可以显示在特定细胞网络中哪些基因受到了影响. 目的應用繫統生物學方法,研髮一種基于轉錄組錶達譜的基因網絡可視化工具,以直觀顯示急性心肌梗死後早期的轉錄組和代謝調控的整體變化.方法在美國國立衛生研究中心(NCBI) GEO數據庫下載編號為GDS2331的一箇急性心肌梗死後大鼠心髒左心室的基因芯片錶達文件,其平檯編號為GPL83.篩選實驗時間在15 min,60 min,4h,12h,24和48 h的假手術和急性心肌梗死模型亞組數據,利用Mathwork bioinformatics toolbox工具包將數據轉化為計算機可讀的結構體.利用模式識彆算法剔除錶達揹景譟聲；最後穫得心肌梗死建模後錶達模式擾動最明顯的基因譜.利用K-mean算法對這些基因進行分類,併進行基因本體分析(gene ontology,GO).進而將有關通路標定在京都基因和基因組百科數據庫(kyoto encyclopedia of genes and genomes,KEGG)中,形成基因組-錶達譜繫統分析.結果共有1400箇基因被篩選齣來.在損傷後的前48 h,這些基因的變化模式可歸為16類.根據可以穫得基因本體分析髮現:在生物學過程上,心肌梗死後早期調控髮生改變主要和髮育基因相關,其中主要包括蛋白激酶B信號傳導途徑,中樞神經繫統髮育途徑,以及cytochalasin B調控相關途徑.在分子功能上,這些功能主要和燐痠化,肌動蛋白的結閤以及覈痠的配對解離有關.在細胞成分上,主要與細胞內外膜相結構之間的聯繫、高爾基複閤體、齣胞作用、以及細胞骨架特彆是dynactin complex等結構有關.KEGG作圖標記可顯示在分子調控傳導路徑噹中,受到影響的基因很可能通過該傳導通路的上下遊分子進行調控.如以肌動蛋白為覈心的細胞骨架信息傳導途徑的調控中,GF RTK Vav/tiam Rac mlCK Myosin整箇調控途徑中的分子都有相同的調控模式.結論利用繫統生物學技術可以實現急性心肌梗死後基因錶達波動模式的可視化描述.這些模式可以反映基因錶達在不同時間點質和量上的錶達差異.結閤Geneontology的基因語義功能學上的研究和基于KEGG的作圖法是一種有力的聯閤分析工具,前者可以直觀的展示擾動的基因在功能上的共同點,後者可以顯示在特定細胞網絡中哪些基因受到瞭影響.
목적 응용계통생물학방법,연발일충기우전록조표체보적기인망락가시화공구,이직관현시급성심기경사후조기적전록조화대사조공적정체변화.방법 재미국국립위생연구중심(NCBI) GEO수거고하재편호위GDS2331적일개급성심기경사후대서심장좌심실적기인심편표체문건,기평태편호위GPL83.사선실험시간재15 min,60 min,4h,12h,24화48 h적가수술화급성심기경사모형아조수거,이용Mathwork bioinformatics toolbox공구포장수거전화위계산궤가독적결구체.이용모식식별산법척제표체배경조성；최후획득심기경사건모후표체모식우동최명현적기인보.이용K-mean산법대저사기인진행분류,병진행기인본체분석(gene ontology,GO).진이장유관통로표정재경도기인화기인조백과수거고(kyoto encyclopedia of genes and genomes,KEGG)중,형성기인조-표체보계통분석.결과 공유1400개기인피사선출래.재손상후적전48 h,저사기인적변화모식가귀위16류.근거가이획득기인본체분석발현:재생물학과정상,심기경사후조기조공발생개변주요화발육기인상관,기중주요포괄단백격매B신호전도도경,중추신경계통발육도경,이급cytochalasin B조공상관도경.재분자공능상,저사공능주요화린산화,기동단백적결합이급핵산적배대해리유관.재세포성분상,주요여세포내외막상결구지간적련계、고이기복합체、출포작용、이급세포골가특별시dynactin complex등결구유관.KEGG작도표기가현시재분자조공전도로경당중,수도영향적기인흔가능통과해전도통로적상하유분자진행조공.여이기동단백위핵심적세포골가신식전도도경적조공중,GF RTK Vav/tiam Rac mlCK Myosin정개조공도경중적분자도유상동적조공모식.결론 이용계통생물학기술가이실현급성심기경사후기인표체파동모식적가시화묘술.저사모식가이반영기인표체재불동시간점질화량상적표체차이.결합Geneontology적기인어의공능학상적연구화기우KEGG적작도법시일충유력적연합분석공구,전자가이직관적전시우동적기인재공능상적공동점,후자가이현시재특정세포망락중나사기인수도료영향.
Objective Establishing a visualization tool to examine global gene expression regulatory networks changes after acute myocardial infractions (AMI).Methods We used a gene microarray dataset named GDS 2331.It contained gene expression profiling data for rat AMI modeling (the platform number is GPL 83).This data set was downloaded in a National Center for Biotechnology Information (NCBI) GEO database.We isolated datasets that contained gene expression profiles at 15 min,60 min,4 hours,12 hour,14 hours and 48 hours after AMI.We transformed the original data into computer readable structures for Matlab using Mathworks Bioinformatics Toolbox.The pattern recognition algorithm diminished background noise,and we got a significant gene expression disturbances spectrum.K-mean clustering was used to distinguish patterns of gene expressions.We used gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) platform to establish the connection between transcriptomics and metabolic systems.Results In total 1,400 genes were selected for modeling.We found that during the first 48 hours after AMI,the changes in these genes could be categorized into 16 expression patterns.According to Gene Ontology analysis,we found:(1) in biological processing,there is a set of developmental related genes in which the regulatory status changed significantly that includes protein kinase B path,central nerve development path and cytochalasin B regulatory path; (2) in molecule functions,the changes were related to phosphorylation,actin binding and nucleic acid pairing/unzipping; (3) in cellular components,the changes were related with intra-cellular and inter-cellular membrane structures,exocytosis and cellular skeletons (especially related with dynactin complex).KEGG mapping successfully exhibited regulatory paths and identified the sites of regulation and discovered similar regulatory patterns in up-stream and/or down-stream genes.For example,when we found that actin was a core site for cellular skeleton signaling regulation,similar regulatory pattern existed at GF RTK Vav/tiam Rac MLCK Myosin paths.Conclusions We conclude that systematically biological method provides visualization tools to describe gene expression pattern changes after AMI.These patterns reflect profiling dynamics that integrates expression volume and sites.When we use gene ontology analysis and KEGG mapping,we get a powerful integrated tool that synchronously exhibits functional and locational information on gene expression regulatory networks.